Purpose: This paper is aimed at developing a regression tree model useful to quantify the Money Laundering (ML) risk associated to a customer profile and his contracted products (customer’s inherent risk). ML is a risk to which different entities are exposed, but mainly the financial ones...

This paper identifies and quantifies through a Bayesian Network model (BN) the various factors of Operational Risk (OR) associated with business lines of transnational banks. The BN model is calibrated with data from events that occurred in different lines of business of such banks during...

Purpose This paper aims to develop a money laundering risk management model for multiple-purpose financial institutions (SOFOMES, Spanish acronym for “Sociedades Financieras de Objeto Múltiple”) based on the best international practices. Design/methodology/approach A study of a sample of...